SKILL.md
Create a strategy comparison script.
Arguments
Parse $ARGUMENTS as: symbol followed by strategy names
$0= symbol (e.g., SBIN, RELIANCE, NIFTY)- Remaining args = strategies to compare (e.g., ema-crossover rsi donchian)
If only a symbol is given with no strategies, compare: ema-crossover, rsi, donchian, supertrend. If "long-vs-short" is one of the strategies, compare longonly vs shortonly vs both for the first real strategy.
Instructions
- Read the vectorbt-expert skill rules for reference patterns
- Create
backtesting/strategy_comparison/directory if it doesn't exist (on-demand) - Create a
.pyfile inbacktesting/strategycomparison/named{symbol}strategy_comparison.py - The script must:
- Fetch data once via OpenAlgo - If user provides a DuckDB path, load data directly via duckdb.connect(path, readonly=True). See vectorbt-expert rules/duckdb-data.md. - If openalgo.ta is not importable (standalone DuckDB), use inline exrem() fallback. - Use OpenAlgo ta for ALL indicators by default (never VectorBT built-in). Only switch to TA-Lib if the user explicitly says "talib"/"TA-Lib" - Always use OpenAlgo ta for specialty indicators (Supertrend, Donchian, etc.) - no TA-Lib equivalent exists - Clean signals with ta.exrem() (always .fillna(False) before exrem) - Run each strategy on the same data - Indian delivery fees: fees=0.00111, fixedfees=20 for delivery equity - Collect key metrics from each into a side-by-side DataFrame - Include NIFTY benchmark in the comparison table (via OpenAlgo NSEINDEX) - Print Strategy vs Benchmark comparison table: Total Return, Sharpe, Sortino, Max DD, Win Rate, Trades, Profit Factor - Explain results in plain language - which strategy performed best and why - Plot overlaid equity curves for all strategies using Plotly (template="plotlydark") - Save comparison to CSV
- Never use icons/emojis in code or logger output
Example Usage
/strategy-compare RELIANCE ema-crossover rsi donchian /strategy-compare SBIN long-vs-short ema-crossover